The ideal candidate should have the passion to use healthcare data and advanced machine learning techniques to build services to patients and caregivers. We are building an end-to-end service that integrates seamlessly into the lives of those patients via multiple touchpoints on front-end while providing intelligent analytics on the backend.
- Research and develop the medical NLP technique. It's especially designed to extract key information including doctor's diagnosis, recommendations, outcome, endpoints from free-form clinical texts (or electronic medical records) which contains acronyms, abbreviations and typing errors.
- Research and develop the medical NLP technique to categorise the clinical text data for systematic access and research and summarise the text by natural language processing for a group of patients that researchers to identify medical symptoms and treatments.
- Documentation which clearly explains how algorithms have been implemented, verified and validated.
- Draft and apply paper publications.
- Edit or review task-related research documents.
Experience / Training:
- Hands on experience in medical natural language processing models and tools, including widely used machine learning / deep learning models, etc.
- Knowledge in medical semantic technology; background in or exposure to healthcare data, human physiology or cardiology is good to have.
- Proficient with natural language processing techniques, including but not limited to semantic analysis, intention recognition, human-machine dialogue, named entity recognition, clustering, etc.
- Proficient with programming in Python. Programming in C/C++ is a plus.
- Experience with medical NLP. Familiar with one type of clinical texts (electronic medical records) is a plus.
- Master or PhD in Biomedical Engineering, Computer Science, Medical Information Engineering, Electronic Engineering or related fields with coding skills and understanding for electronic medical records.
Arvin Clark Sikat, Sombilla EA License No.: 02C3423 Personnel Registration No.: R1222536